| The promise repository of empirical software engineering data T Menzies, B Caglayan, E Kocaguneli, J Krall, F Peters, B Turhan June, 2012 | 458 | 2012 |
| On the value of ensemble effort estimation E Kocaguneli, T Menzies, JW Keung IEEE Transactions on Software Engineering 38 (6), 1403-1416, 2011 | 328 | 2011 |
| Exploiting the essential assumptions of analogy-based effort estimation E Kocaguneli, T Menzies, A Bener, JW Keung IEEE transactions on software engineering 38 (2), 425-438, 2011 | 248 | 2011 |
| Software effort models should be assessed via leave-one-out validation E Kocaguneli, T Menzies Journal of Systems and Software 86 (7), 1879-1890, 2013 | 180 | 2013 |
| Software effort models should be assessed via leave-one-out validation E Kocaguneli, T Menzies Submitted to Empirical Software Engineering, 2011 | 180 | 2011 |
| Active learning and effort estimation: Finding the essential content of software effort estimation data E Kocaguneli, T Menzies, J Keung, D Cok, R Madachy IEEE Transactions on software engineering 39 (8), 1040-1053, 2012 | 115 | 2012 |
| Transfer learning in effort estimation E Kocaguneli, T Menzies, E Mendes Empirical Software Engineering 20, 813-843, 2015 | 104 | 2015 |
| Defect prediction between software versions with active learning and dimensionality reduction H Lu, E Kocaguneli, B Cukic 2014 IEEE 25th International Symposium on Software Reliability Engineering …, 2014 | 95 | 2014 |
| Finding conclusion stability for selecting the best effort predictor in software effort estimation J Keung, E Kocaguneli, T Menzies Automated Software Engineering, 1-25, 2012 | 92 | 2012 |
| Sharing data and models in software engineering T Menzies, E Kocaguneli, B Turhan, L Minku, F Peters Morgan Kaufmann, 2014 | 90 | 2014 |
| When to use data from other projects for effort estimation E Kocaguneli, G Gay, T Menzies, Y Yang, JW Keung Proceedings of the 25th IEEE/ACM International Conference on Automated …, 2010 | 73 | 2010 |
| How to find relevant data for effort estimation? E Kocaguneli, T Menzies 2011 International Symposium on Empirical Software Engineering and …, 2011 | 64 | 2011 |
| Kernel methods for software effort estimation: Effects of different kernel functions and bandwidths on estimation accuracy E Kocaguneli, T Menzies, JW Keung Empirical Software Engineering 18, 1-24, 2013 | 58 | 2013 |
| Prest: An Intelligent Software Metrics Extraction, Analysis and Defect Prediction Tool. E Kocaguneli, A Tosun, AB Bener, B Turhan, B Caglayan SEKE, 637-642, 2009 | 46 | 2009 |
| Distributed development considered harmful? E Kocaguneli, T Zimmermann, C Bird, N Nagappan, T Menzies 2013 35th International Conference on Software Engineering (ICSE), 882-890, 2013 | 42 | 2013 |
| Using goals in model-based reasoning T Menzies, E Kocagüneli, L Minku, F Peters, B Turhan Sharing Data and Models in Software Engineering 1, 321-353, 2015 | 41 | 2015 |
| Combining multiple learners induced on multiple datasets for software effort prediction E Kocaguneli, Y Kultur, A Bener International symposium on software reliability engineering (ISSRE), 2009 | 41 | 2009 |
| Ai-based models for software effort estimation E Kocaguneli, A Tosun, A Bener 2010 36th EUROMICRO Conference on Software Engineering and Advanced …, 2010 | 33 | 2010 |
| The inductive software engineering manifesto: principles for industrial data mining T Menzies, C Bird, T Zimmermann, W Schulte, E Kocaganeli Proceedings of the International Workshop on Machine Learning Technologies …, 2011 | 29 | 2011 |
| Building a second opinion: learning cross-company data E Kocaguneli, B Cukic, T Menzies, H Lu Proceedings of the 9th International Conference on Predictive Models in …, 2013 | 21 | 2013 |